Solar neighborhoods: the impact of urban layout on a large-scale solar strategies application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The article addresses the challenges of evaluating energy performance in different neighborhood settings under various energy efficiency measures and proposes a methodology for selecting appropriate solar strategies on a neighborhood scale. The study selects five representative neighborhoods from various climatic zones with different building and street layouts. The proposed methodology involves a systematic three-step multi-domain workflow for implementing energy efficiency measures and solar strategies in the existing neighborhoods. The first step involves typical energy performance simulation, the second step involves energy simulation using high performance building envelope, and the third step involves the addition of solar strategies in combination with retrofitting materials to achieve net-zero status. The results of the study show that modifying the building envelope leads to a significant reduction in energy consumption, with up to 60% reduction observed. The study also finds that the optimal mix of solar strategies depends strongly on the type of neighborhood, its street layouts, and the type of buildings. The article highlights the importance of considering these factors when implementing solar strategies on a neighborhood scale to achieve energy efficiency and net-zero status. It provides urban planners with a systematic decision-making approach to evaluate and optimize neighborhoods to achieve net-zero energy status.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it